Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Trong-Nghia/roberta-large-detect-dep-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trong-Nghia/roberta-large-detect-dep-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Trong-Nghia/roberta-large-detect-dep-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Trong-Nghia/roberta-large-detect-dep-v3") model = AutoModelForSequenceClassification.from_pretrained("Trong-Nghia/roberta-large-detect-dep-v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9554cfc19b0802a7208ee88c1300aa9a488af2b3ebccd5b5ab232a517a9c5c02
- Size of remote file:
- 4.03 kB
- SHA256:
- fce9859752daa10529a1a6f94ec4477ca1c8903c203e3df59ee638cc570614df
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